The mixed integer robust maximum expert consensus models for large-scale GDM under uncertainty circumstances - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Shaojian Qu, Yuanming Li, Ying Ji. The mixed integer robust maximum expert consensus models for large-scale GDM under uncertainty circumstances. Appl. Soft Comput., 107:107369, 2021. [doi]

The following publications are possibly variants of this publication:

The Novel Data-Driven Robust Maximum Expert Mixed Integer Consensus Models Under Multirole's Opinions Uncertainty by Considering NoncooperatorsJinpeng Wei, Shaojian Qu, Qiuhan Wang, Dongqing Luan, Xiaohui Zhao. tcss, 10(6):3454-3470, December 2023. [doi]

Robust two-stage minimum asymmetric cost consensus models under uncertainty circumstancesYing Ji, Yingying Li, Chethana Wijekoon. isci, 663:120279, 2024. [doi]

Robust maximum expert consensus model with adjustment path under uncertain environmentYifan Ma, Ying Ji, Chethana Wijekoon. asc, 155:111430, 2024. [doi]

Consensus modeling for maximum expert with quadratic cost under various uncertain contexts: A data-driven robust approachJinpeng Wei, Xuanhua Xu, Shaojian Qu, Qiuhan Wang. eor, 323(1):192-207, 2025. [doi]

Bias correction for multiple covariate analysis using empirical bayesian estimation in mixed-effects models for longitudinal dataYi Li, Yaning Yang, Xu Steven Xu, Min Yuan, for the Alzheimer's Disease Neuroimaging Initiative. CANDC, 99:107697, 2022. [doi]

runs on WebDSL